Int. J. of Cloud Computing   »   2015 Vol.4, No.1

 

 

Title: Collaborative knowledge as a service applied to the disaster management domain

 

Authors: Katarina Grolinger; Emna Mezghani; Miriam A.M. Capretz; Ernesto Exposito

 

Addresses:
Faculty of Engineering, Department of Electrical and Computer Engineering, Western University, London, ON, N6A 5B9, Canada
CNRS, LAAS, 7 av. du Colonel Roche, F-31400 Toulouse, France; UPS, INSA, INP, ISAE, LAAS, Université de Toulouse, F-31400 Toulouse, France
Faculty of Engineering, Department of Electrical and Computer Engineering, Western University, London, ON, N6A 5B9, Canada
CNRS, LAAS, 7 av. du Colonel Roche, F-31400 Toulouse, France; UPS, INSA, INP, ISAE, LAAS, Université de Toulouse, F-31400 Toulouse, France

 

Abstract: Cloud computing offers services which promise to meet continuously increasing computing demands by using a large number of networked resources. However, data heterogeneity remains a major hurdle for data interoperability and data integration. In this context, a knowledge as a service (KaaS) approach has been proposed with the aim of generating knowledge from heterogeneous data and making it available as a service. In this paper, a collaborative knowledge as a service (CKaaS) architecture is proposed, with the objective of satisfying consumer knowledge needs by integrating disparate cloud knowledge through collaboration among distributed KaaS entities. The NIST cloud computing reference architecture is extended by adding a KaaS layer that integrates diverse sources of data stored in a cloud environment. CKaaS implementation is domain-specific; therefore, this paper presents its application to the disaster management domain. A use case demonstrates collaboration of knowledge providers and shows how CKaaS operates with simulation models.

 

Keywords: cloud computing; data integration; data heterogeneity; knowledge as a service; KaaS; NoSQL storage; disaster management; data interoperability; collaborative knowledge; emergency management; simulation; modelling.

 

DOI: 10.1504/IJCC.2015.067706

 

Int. J. of Cloud Computing, 2015 Vol.4, No.1, pp.5 - 27

 

Available online: 23 Feb 2015

 

 

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